1. Technical Field
The present invention relates generally to processing control data, and more particularly relates to managing reliability data collected from an industrial plant.
2. Related Art
Like most large-scale industrial operations, modern power plants require a tremendous amount of scheduled maintenance to operate at peak efficiency. Typical maintenance involves inspecting turbine parts, analyzing inspection data, calculating expected lifespan of parts, and replacing and/or servicing parts. Given the costs involved in providing such services, effectively managing the maintenance processes can have a substantial impact on plant profitability.
One specific challenge with servicing power plants involves how to collect and utilize data necessary to make intelligent maintenance decisions, such as when parts should be replaced, etc. However, because of the number of parts and variables that exist for maintaining a complicated system such as a gas turbine, automation of the maintenance process is a complex problem. While systems exist for tracking parts and maintenance histories (i.e., static data), the life expectancy of each component is going to depend greatly on numerous operational characteristics that the component was subject to (e.g., hours of operation, starts, etc.). Therefore, tracking parts life requires measuring and tracking not only the parts themselves, but also the operational characteristics of hundreds or thousands of parts, which represents a significant challenge.
Power plants generate thousands of raw operational data points (i.e., dynamic data) each second including, e.g., temperature measurements, turbine speed, trips, hours of operation, fuel consumption, startup information, etc. The mere act of capturing and storing thousands of raw data points in a near real-time environment can require significant computing resources. This, combined with the need to provide analysis and storage tools to convert the data into some useful information creates significant data processing obstacles.
Accordingly, in order to provide an automated and comprehensive maintenance program, all reliability data including both dynamic data (operational information) and static data (part information and general maintenance records) must be carefully tracked and incorporated into any reliability analysis. Moreover, even if such comprehensive reliability data exists, such records may exist only in manual logs and/or in disparate electronic formats. Accordingly, numerous challenges exist with respect to effectively maintaining large-scale control operations, such as power plants. Without an automated system for more effectively managing reliability information, maintaining such plants will remain an inefficient process.